mobility of patients within healthcare institutions inês videira, inês jorge, iolanda ferreira,...

Mobility of patients within Healthcare

Institutions

Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer

Pires, Joana Ribeiro, Joana Vaz, Joana Fernandes, Joana Costa,

Joana Magalhães

Faculdade de Medicina da Universidade do

Porto

Introdução à Medicina

Turma 10

2005/2006

Mobility of patients within Healthcare Institutions

Presentation Summary

Introduction

Objective

Methods

Results/Discussion

Discussion Synthesis

Limitations - Bias


Objective

To study patients’ mobility within

healthcare institutions.


Study Classification

Analytic: relates the variables in study

Observational: studies the characteristics of the

target population

Transversal: data is collected in a single moment

Retrospective: information refers to the previous

year Analysis Unit: all the individuals over 65

years old per household

Methods


Sample design

Random sample of 83 adult individuals out of the available population

Methods

Target population: individuals over 65 years old of Oporto region (Espinho, Gondomar, Matosinhos, Maia, Oporto, Paredes, Stª Maria da Feira, Trofa, Valongo, Vila do Conde, Vila Nova de Gaia) Available population: individuals over 65 years old of Oporto region with household phone number starting with 22.


Methods Data collection

Random Digit Dialling – revision of the method by Mitofsky and Waksberg

Questionnaire design The questionnaire included sociodemographic characteristics (age, sex, city)

Questions related to the subject in study.

Scale pilot - interview with six subjects, in which the five questions were developed


Methods

Statistic Issues

Simple frequency distribution - to show the characteristics of the subjects and their answers

Variance was calculated for every variable. Relations between variables were defined using cross tabs and multiple response tables

Analyses performed with SPSS for Windows 13.0


Results/Discussion

Sample Results: 56 women and 26 men

Mean number of age 72.6 years old

Ages between 65 and 89 years old

Results/Discussion

The mean number of different healthcare institutions visited in 2005 was 4.8

People go to different types of institutions or to different institutions within the same type?


Table 1 – Mean numbers of attended healthcare institutions, within the same type, by men and women separately and both genders together.

Results/Discussion

The median of healthcare institutions attended to within the same type is one.

People usually go to one medical institution per type.

Hospitals

Health Centres

Private Laboratories

Private Physicians

Pharmacies

Men 0,81 0,69 0,92 0,96 1,15

Women 1,13 0,86 0,96 0,68 1,34

Both Genders

1,04 0,80 0,94 0,76 1,27


Results/Discussion

Hospitals: 25% went to more than one hospital vs 51%

that only went to one hospital Health Centres:

Low variability – only 5% attended more than one institution

Pharmacies: 28% went to more than one pharmacy vs 57%

that went to one


Number of distinct types of institutions

1 2 3 4 5

Number of people 2 (2%) 8 (10%) 22 (27%) 30 (36%) 21 (25%)

Table 2 – Number of types of institutions visited and the corresponding amount of people who visited them.

Results/Discussion

61% of the individuals go to more than three distinct types of healthcare institutions – existence of certain mobility.


Table 3 – H: Hospitals; PL: Private laboratories; HC: Health Centres; PP: Private Physicians; P: Pharmacies; Y/Y: Went to both institutions; N/N: Attended none of the institutions; Y/N; Attended only one of the institutions. The results presented in the table regard the 83 questionnaires obtained.

Crossing of 2 different healthcare

institutionsY/Y N/N Y/N

P + PL 56 (67%) 3 (4%) 24 (29%)

HC + P 54 (66%) 6 (7%) 23 (27%)

H + P 52 (63%) 2 (2%) 29 (35%)

HC + PL 51 (61%) 7 (8%) 25 (31%)

H + PL 50 (60%) 4 (5%) 29 (35%)

H + HC 50 (60%) 9 (11%) 24 (29%)

P + PP 40 (48%) 4 (5%) 39 (47%)

PL + PP 40 (48%) 8 (10%) 35 (42%)

H + PP 37 (45%) 8 (10%) 38 (45%)

HC + PP 34 (41%) 7 (8%) 42 (51%)

Doctors

Private Labs

Pharmacies

Results/Discussion


Based on the statistics there should be an exchange of medical information between pharmacies and private labs, provided by information systems.

The previous institutions are intrinsically linked to physicians, therefore with the public places where they work.

Hospitals, health centres, private labs and pharmacies, should be informatically linked, because more than 60% of the individuals attended each association of two institutions.

Results/Discussion


Results/Discussion

Lapa

Trindade

Carmo

Terço

Vila_Real

Vale_Sousa

Guimarães

Vila_Conde

Valongo

Póvoa

Matosinhos

Pedro_Hispano

VNG

CHVNG

Prelada

Joaquim_Urbano

IPO

HSA

HSJ

Of the 83 inquired individuals:

20 (24%)didn’t go to any hospital;

63 (76%) went to at least one.

HSJ: 30%

VNG: 24%

HSA: 21%


Results/Discussion

Of the 19 inquiries that went to HSJ:

4 (21%) also attended HSA;

2 (10%) went to IPO as well;

2 attended Hospital de Valongo.


Results/Discussion

Men and Women – are there any differences? Women often go, in average, to more

health institutions than men. This difference is not significant – our

sample is too small. Statement supported by values of

median (equals one, in both men and women separately).


Discussion Synthesis

Patients’ mobility has been registered: More pronounced between different types

of healthcare institutions Less distinct among the same type of

medical institutions

Patients would indeed benefit from an information linkage between different types of healthcare institutions


Discussion Synthesis If there is to exist information systems

that link different medical institutions, those should preferably be: Pharmacies and Private Laboratories: 67% Health Centres and Pharmacies: 66% Hospitals and Pharmacies: 63% Health Centres and Private Laboratories:

61% Hospitals and Private Laboratories: 60% Hospitals and Health Centres: 60%


Not every individual in target population owns a

household phone number

Restricted time period of interviews

Limitations - Bias

Some of the phone numbers starting with 22

include places out of the Oporto region

Data collected in one moment may not also reflect

the reality due to people’s memory lapses

Individuals that refuse to participate

mobility of patients within healthcare institutions inês videira, inês jorge, iolanda ferreira,...

Documents

mobility of patients

healthcare institutions

different institutions

study patients mobility

years old slide

years old ages

household methods

joana ribeiro